DeepAgents: AI That Works for Hours, Not Seconds
Most AI agents answer a question and move on. DeepAgents stay on the job. They run for minutes or hours, calling APIs, pulling data from multiple systems, and completing multi-step tasks that used to require a human sitting at a screen all day.
Not a Chatbot. A Persistent Worker.
A DeepAgent receives an objective, breaks it into steps, executes each one, and adapts when something goes wrong. It keeps its full context the entire time.
Runs Until the Job Is Done
A customer sends a billing dispute that involves checking three systems, verifying transaction history, and applying a partial refund. A DeepAgent handles the entire flow in one go, even if it takes 20 minutes.
Thinks in Steps, Not Single Answers
When a task requires checking eligibility, then looking up inventory, then processing a return, a DeepAgent sequences those steps and adjusts the plan if one of them returns unexpected data.
What You Can Build With DeepAgents
The building blocks that make long-running AI tasks possible.
API Orchestration
Chain calls to your CRM, payment system, and warehouse API in sequence. The agent handles auth, retries, and passes data between each call.
Cross-System Research
Pull information from your knowledge base, past tickets, and product docs to build a complete picture before responding to a customer.
Process Execution
Run a full return workflow: check the policy, verify the order, coordinate with logistics, process the refund, and notify the customer.
Live Decision Making
If an API call fails or a condition changes mid-task, the agent re-evaluates its plan and picks a different path forward.
Task Decomposition
Give it a high-level goal like 'resolve this escalated ticket' and it figures out the steps: gather context, check systems, draft a response, get approval.
Full Context Retention
Every piece of data the agent gathers during a task stays in its memory. Step 8 can reference what it learned in step 2.
What Teams Actually Use DeepAgents For
Real workflows that used to require a support agent spending 30 minutes per case.
Billing Disputes
A customer says they were charged twice. The agent pulls the transaction history, checks the payment gateway, compares with the order system, identifies a duplicate charge, and processes the refund. Total time: 3 minutes instead of 25.
Returns and Exchanges
The agent verifies the return window, checks the item condition policy, coordinates a pickup with the logistics partner, issues a store credit or refund based on the customer's preference, and sends tracking info.
Technical Troubleshooting
A user reports a bug. The agent searches the knowledge base, checks if the issue is known, looks at the user's account configuration, tests a fix in the sandbox, and walks the user through the solution.
Escalation Handoffs
When a case needs a human, the agent gathers every piece of context first: full conversation history, account status, what was already tried, and a recommended next step. The human agent picks up with zero ramp-up time.
How a DeepAgent Runs a Task
From receiving an objective to delivering the result, here is what happens.
Understand and Plan
The agent reads the objective, identifies which systems it needs to query, and builds an execution plan with fallback paths in case something fails.
Execute and Adapt
It runs each step, checks the result, and moves on. If an API returns an error or the data looks wrong, the agent retries or takes a different route.
Deliver the Outcome
Once every step is complete, the agent delivers the result: a resolved ticket, a processed refund, a detailed report, or whatever the task required.
Everything Stays in Memory
A DeepAgent remembers every API response, every piece of customer data, and every decision it made during the task. When step 5 needs information from step 1, it is already there. No context is lost.
What Changes When You Deploy DeepAgents
The impact our customers see after switching from chatbots to persistent agents.
Complex Cases Get Resolved Automatically
The cases that used to sit in a queue for hours because they required checking multiple systems now get handled in minutes without human intervention.
Support Teams Focus on What Matters
When the repetitive multi-step work is off their plate, your team spends their time on cases that actually require human judgment and empathy.
Consistent Quality at Any Volume
Whether you get 50 or 5,000 complex cases a day, every one follows the same thorough process. No steps skipped because someone was in a rush.
Ready to Try DeepAgents?
Pick one workflow that takes your team too long today. We will set up a DeepAgent to handle it end to end and show you the results in a live pilot.